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Bayesian decision network modeling for environmental risk management: A wildfire case study.
J Environ Manage. 2020 Sep 15;270:110735. doi: 10.1016/j.jenvman.2020.110735. Epub 2020 Jun 10.
J Environ Manage. 2020.
PMID: 32721285
Improved accuracy of wildfire simulations using fuel hazard estimates based on environmental data.
Penman TD, McColl-Gausden SC, Cirulis BA, Kultaev D, Ababei DA, Bennett LT.
Penman TD, et al. Among authors: cirulis ba.
J Environ Manage. 2022 Jan 1;301:113789. doi: 10.1016/j.jenvman.2021.113789. Epub 2021 Sep 27.
J Environ Manage. 2022.
PMID: 34592661
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Developing and testing models of the drivers of anthropogenic and lightning-caused wildfire ignitions in south-eastern Australia.
Clarke H, Gibson R, Cirulis B, Bradstock RA, Penman TD.
Clarke H, et al. Among authors: cirulis b.
J Environ Manage. 2019 Apr 1;235:34-41. doi: 10.1016/j.jenvman.2019.01.055. Epub 2019 Jan 19.
J Environ Manage. 2019.
PMID: 30669091
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The 2019-2020 Australian forest fires are a harbinger of decreased prescribed burning effectiveness under rising extreme conditions.
Clarke H, Cirulis B, Penman T, Price O, Boer MM, Bradstock R.
Clarke H, et al. Among authors: cirulis b.
Sci Rep. 2022 Jul 13;12(1):11871. doi: 10.1038/s41598-022-15262-y.
Sci Rep. 2022.
PMID: 35831432
Free PMC article.
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